Information Feedback Based Architecture for Handling the Scalability Issues in the Reusable Cloud Components

Author(s):  
Manjunath Ramachandra ◽  
Pandit Pattabhirama

With the evolution of the paradigm of cloud computing in every field of application, the demand on the reusable resources while providing the service has increased substantially. Although it is transparent to the user through virtualization, that is also a strength of cloud computing, the runtime scalability of resources to cater for a variety of services is to be addressed to meet the critical factor of the agreed quality of service. In this work, an architecture based on information feedback is presented to address this issue. The findings have been supported by the simulation results. The scalable architecture makes use of a hierarchy of resources, each level capable of providing a different degree of services. The demand for resources at each level, which is also equivalent to contention for resources or service drops, is computed using Random Early Detection (RED) or similar algorithms and used as feedback signal. The effectiveness of this signal may be enhanced by predicting the same several steps ahead of time. The prediction ensures the availability of a breathing time for the allocation of the resources.

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1400
Author(s):  
Muhammad Adnan ◽  
Jawaid Iqbal ◽  
Abdul Waheed ◽  
Noor Ul Amin ◽  
Mahdi Zareei ◽  
...  

Modern vehicles are equipped with various sensors, onboard units, and devices such as Application Unit (AU) that support routing and communication. In VANETs, traffic management and Quality of Service (QoS) are the main research dimensions to be considered while designing VANETs architectures. To cope with the issues of QoS faced by the VANETs, we design an efficient SDN-based architecture where we focus on the QoS of VANETs. In this paper, QoS is achieved by a priority-based scheduling algorithm in which we prioritize traffic flow messages in the safety queue and non-safety queue. In the safety queue, the messages are prioritized based on deadline and size using the New Deadline and Size of data method (NDS) with constrained location and deadline. In contrast, the non-safety queue is prioritized based on First Come First Serve (FCFS) method. For the simulation of our proposed scheduling algorithm, we use a well-known cloud computing framework CloudSim toolkit. The simulation results of safety messages show better performance than non-safety messages in terms of execution time.


Author(s):  
Ge Weiqing ◽  
Cui Yanru

Background: In order to make up for the shortcomings of the traditional algorithm, Min-Min and Max-Min algorithm are combined on the basis of the traditional genetic algorithm. Methods: In this paper, a new cloud computing task scheduling algorithm is proposed, which introduces Min-Min and Max-Min algorithm to generate initialization population, and selects task completion time and load balancing as double fitness functions, which improves the quality of initialization population, algorithm search ability and convergence speed. Results: The simulation results show that the algorithm is superior to the traditional genetic algorithm and is an effective cloud computing task scheduling algorithm. Conclusion: Finally, this paper proposes the possibility of the fusion of the two quadratively improved algorithms and completes the preliminary fusion of the algorithm, but the simulation results of the new algorithm are not ideal and need to be further studied.


Author(s):  
Muhammad Usman Ashraf ◽  
◽  
Sabah Arif ◽  
Abdul Basit ◽  
Malik Sheraaz Khan

2020 ◽  
Vol 3 (2) ◽  
pp. 348-356
Author(s):  
Sutikno Sutikno ◽  
Sandu Siyoto ◽  
Byba Melda Suhita

Hospitals are required to always improve the quality of service provided to patients. These challenges have forced the hospital to develop its ability to manifest in various aspects of health care quality responsible. One of them by applying the assessment and early detection in patients kegawatan as well as the critical state of activation becomes very important. Quick and proper response to a nurse against the worsening conditions of patients giving a great impact to the quality of the quality of service provided. The purpose of this research is to analyze the implementation of Early Warning systems (EWSS) Score against AvLOS and trust patients in Inpatient installation at Jombang General Hospitals. The research design was analytic observational with a quantitative approach. Research variables i.e. implementation of EWSS as independent variables. AvLos and trust patients as the dependent variable. The population of this entire research nurses in Inpatient installation at Jombang General Hospitals as much as 135 nurses, patients and families of patients who are being treated in Inpatient installation at Jombang General Hospitals Jombang. Samples taken with the cluster random sampling technique as much as 101 respondents. Data is collected with instruments ceklist and processed in coding, editing, tabulating and scoring as well as tested with logistics regression test. Logistic regression results indicate that partially and simultaneously show that the value of p values < 0.05 so that there were the implementation of Early Warning systems (EWSS) Score against AvLOS and trust of the patient, and the simultaneous influence of 83.2%. The existence of implementation of EWSS in patients with good then early detection and response officers can be done in a proper and effective against the condition and the healing of patients and can shorten the day care patients, so that it can affect the confidence and trust family and patient in receiving health services in the hospital


With traffic increase in a wireless network beyond its capacity and as the number of connected devices continue to grow, the quality of service (QoS) degrades. In this paper we study the impact of mobility on throughput in the case of an infrastructure wireless network using IEEE 802.11 Wi-Fi standard. Since we found in the literature that the mobility of stations can have an impact on the quality of service, we try to remedy to this by implementing a new access category reserved for mobile stations. First we compare the throughput between static and mobile nodes, both connected to a QoS station. Then we propose our new model that consists of adding a new access category used by mobile nodes regardless of their traffic category. The study was made by simulating different scenarios using Network Simulator-3 (NS-3). We found that the throughput may vary depending on the simulation scenario. The simulation results show that with the proposed solution the mobile nodes can have a better throughput.


Author(s):  
Mohamed M. Ould Deye ◽  
Mamadou Thiongane ◽  
Mbaye Sene

Auto-scaling is one of the most important features in Cloud computing. This feature promises cloud computing customers the ability to best adapt the capacity of their systems to the load they are facing while maintaining the Quality of Service (QoS). This adaptation will be done automatically by increasing or decreasing the amount of resources being leveraged against the workload’s resource demands. There are two types and several techniques of auto-scaling proposed in the literature. However, regardless the type or technique of auto-scaling used, over-provisioning or under-provisioning problem is often observed. In this paper, we model the auto-scaling mechanism with the Stochastic Well-formed coloured Nets (SWN). The simulation of the SWN model allows us to find the state of the system (the number of requests to be dispatched, the idle times of the started resources) from which the auto-scaling mechanism must be operated in order to minimize the amount of used resources without violating the service-level agreements (SLA).


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